FRcv: Cross-validation scheme for FR models

In gcostaneto/frGIS: Yield adaptability analysis based on factorial regression and environmental covariates

Cross-validation scheme for FR models

Usage

FRcv(df.y, f = 0.2, part.env = 1, intercept = TRUE, boot = 1000,
  seed = 3412, path.output = getwd())

Arguments

df.y

is a data.frame containing the following colunms: environment (factor), genotype (factor), GxE or G+GxE effects (numeric) and covariates (numeric).

f

is a fraction of genotypes that must be used as validation set (default f = 0.2, i.e., 20 \item part.envis the number of environments that be leave out of the training set (0 > part.env > number of environments). Default is 1 (leave-one-out scheme). \item interceptTRUE (default) or FALSE if considering include fixed genotypic intercept \item bootis the number of boots (default is equal to 1000) \item path.outputis the directorie used for output files

Cross-validation scheme for FR models Germano M F Costa Neto

gcostaneto/frGIS documentation built on Jan. 4, 2024, 1:41 p.m.